ArticlePloS one2013
Going the distance for protein function prediction: a new distance metric for protein interaction networks.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.
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Who cites it
66 citing papers in PubMed.
- Comic: explainable drug repurposing via contrastive masking for interpretable connections.BMC bioinformatics · 2026Article
- REPEL - Random Embedding Perturbation for Enhanced Learning of Protein Function.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2026Article
- Integrative multi-omics analysisiScience · 2025Article
- Topology-aware functional similarity: integrating extended neighborhoods via exponential attenuation.BMC bioinformatics · 2025Article
- Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.bioRxiv : the preprint server for biology · 2025Article
- Leveraging transcription factor physical proximity for enhancing gene regulation inference.Bioinformatics (Oxford, England) · 2025Article
- TRENDY: gene regulatory network inference enhanced by transformer.Bioinformatics (Oxford, England) · 2025Article
- Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning.Nature communications · 2025Article
- Common molecular links and therapeutic insights between type 2 diabetes and kidney cancer.PloS one · 2025Article
- Simplicity within biological complexity.Bioinformatics advances · 2025Article
- A foundation model for clinician-centered drug repurposing.Nature medicine · 2024Article
- WeSA: a web server for improving analysis of affinity proteomics data.Nucleic acids research · 2024Article
- Current and future directions in network biology.Bioinformatics advances · 2024Article
- The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations.Biomolecules · 2023Article
- Article
- A network embedding approach to identify active modules in biological interaction networks.Life science alliance · 2023Article
- Gemini: memory-efficient integration of hundreds of gene networks with high-order pooling.Bioinformatics (Oxford, England) · 2023Article
- DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics.Scientific reports · 2023Article
- The module triad: a novel network biology approach to utilize patients' multi-omics data for target discovery in ulcerative colitis.Scientific reports · 2022Article
- NetMix2: A Principled Network Propagation Algorithm for Identifying Altered Subnetworks.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
6 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors.
Funding
Abstract
In protein-protein interaction (PPI) networks, functional similarity is often inferred based on the function of directly interacting proteins, or more generally, some notion of interaction network proximity among proteins in a local neighborhood. Prior methods typically measure proximity as the shortest-path distance in the network, but this has only a limited ability to capture fine-grained neighborhood distinctions, because most proteins are close to each other, and there are many ties in proximity. We introduce diffusion state distance (DSD), a new metric based on a graph diffusion property, designed to capture finer-grained distinctions in proximity for transfer of functional annotation in PPI networks. We present a tool that, when input a PPI network, will output the DSD distances between every pair of proteins. We show that replacing the shortest-path metric by DSD improves the performance of classical function prediction methods across the board.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.